import os
import numpy as np
from specvae.vae import BaseVAE
import specvae.dataset as dt
import specvae.utils as utils
import matplotlib.pyplot as plt
import seaborn as sns
# Parameters
dataset = "MoNA"
# model_name = "jointvae_20-800-200-50-3-50-200-800-20_01 (11-01-2022_23-10-10)"
# model_name = "betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12)"
# model_name = "betavae_capacity_100-400-100-3-400-100_01 (24-12-2021_11-06-17)"
# model_dir = "D:\\Workspace\\SpecVAE\\.model\\MoNA\\jointvae\\jointvae_20-800-200-50-3-50-200-800-20_01 (11-01-2022_23-10-10)"
# model_dir = "d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12)"
# model_dir = "d:\\Workspace\\SpecVAE\\.model\\HMDB\\betavae_capacity_nextron\\betavae_capacity_20-1600-2-1600-20_02 (24-12-2021_18-27-38)"
model_dirs = [
# MoNA
## BetaVAE
### Best
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-400-100-3-400-20_02 (24-12-2021_03-34-34)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-1600-3-1600-20_03 (24-12-2021_00-17-31)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-800-3-800-20_04 (24-12-2021_00-25-10)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_20-100-3-90-100-20_05 (24-12-2021_03-01-19)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\best\\betavae_capacity_50-400-3-100-400-50_06 (24-12-2021_06-19-49)",
### Beta
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_01 (24-12-2021_09-13-36)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_02 (24-12-2021_09-15-11)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_03 (24-12-2021_09-29-26)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_04 (24-12-2021_09-29-36)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_05 (24-12-2021_09-06-14)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\beta\\betavae_capacity_100-1600-200-50-3-50-200-1600-100_06 (24-12-2021_09-05-10)",
### BetaVAE Score
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-100-3-400-100_01 (24-12-2021_11-06-17)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-800-100-3-800-100_02 (24-12-2021_10-59-29)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-200-50-3-50-200-400-100_03 (24-12-2021_09-47-19)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-100-3-400-100_05 (24-12-2021_10-57-01)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\betavae_score\\betavae_capacity_100-400-100-3-100-400-100_06 (24-12-2021_08-41-33)",
### FactorVAE Score
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-100-90-50-3-50-90-100-100_01 (24-12-2021_09-48-37)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-1600-100-3-1600-100_02 (24-12-2021_10-51-41)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-800-100-3-800-100_03 (24-12-2021_11-16-41)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-400-200-50-3-50-200-400-100_05 (24-12-2021_09-23-23)",
"d:\\Workspace\\SpecVAE\\.model\\MoNA\\betavae_capacity_nextron\\factorvae_score\\betavae_capacity_100-1600-100-3-100-1600-100_06 (24-12-2021_08-25-38)",
]
device, cpu = utils.device(use_cuda=True)
GPU device count: 1 Device in use: cuda:0
# print("Load model: %s..." % model_name)
def load_model(path, device):
model_path = os.path.join(path, 'model.pth')
model = BaseVAE.load(model_path, device)
model.eval()
return model
# labels = ['ionization_mode_id', 'collision_energy', 'total_exact_mass', 'precursor_mz', 'instrument_type_id', 'precursor_type_id', 'superclass_id', 'class_id']
if dataset == 'MoNA':
labels = ['collision_energy', 'total_exact_mass']
base_path = utils.get_project_path() / '.data' / 'MoNA'
metadata_path = base_path / 'MoNA_meta.npy'
elif dataset == 'HMDB':
labels = ['collision_energy']
base_path = utils.get_project_path() / '.data' / 'HMDB'
metadata_path = base_path / 'HMDB_meta.npy'
metadata = None
if os.path.exists(metadata_path):
metadata = np.load(metadata_path, allow_pickle=True).item()
# metadata['precursor_type_id']
def load_data(target_column):
# data_path = base_path / ('visualization_%s.csv' % target_column)
data_path = base_path / ('%s_full.csv' % dataset)
df = dt.Spectra.open(data_path)
return df
def preload_data_as_tensor(df, input_columns, types, transform):
# columns = model.config['input_columns']
columns = input_columns
# types = model.config['types']
data = dt.Spectra.preload_tensor(
device=device, data_frame=df[columns + ['id']], transform=transform, limit=-1, types=types, do_print=False)
return data
def evaluate_model(model, df, data):
print("Encode N=%d instances from %s dataset..." % (data['id'].shape[0], dataset))
X, ids = data['spectrum'], data['id'] # TODO: handle the case for concatanated input
Xrecon, z, latent_dist = model.forward_(X)
print(z.shape)
data_np = {}
data_np['X'] = X.data.cpu().numpy()
data_np['Xrecon'] = Xrecon.data.cpu().numpy()
data_np['z'] = z.data.cpu().numpy()
data_np['ids'] = ids
data_np['ionization_mode_id'] = df['ionization_mode_id'].to_numpy()
data_np['collision_energy'] = df['collision_energy'].to_numpy()
# data_np['images'] = df['images'].to_numpy()
return data_np
# import json
# import pandas as pd
# import plotly.express as px
# n_dim = model.latent_dim
# with open(os.path.join(model_dir, 'history.json')) as history:
# history_logs = json.load(history)
# steps = np.array(history_logs['kldiv_cont_0'])[:,0]
# colors = ['kldiv_cont_%d' % dim for dim in range(n_dim)]
# kldivs = dict(zip(colors, [np.array(history_logs['kldiv_cont_%d' % dim])[:,1] for dim in range(n_dim)]))
# kldivs['steps'] = steps
# df = pd.DataFrame(data=kldivs)
# fig = px.line(df, x='steps', y=colors, title='KL Divergence per each cont. dimension')
# fig.show()
from IPython.display import display
df = load_data("")
df = df[
(df['collision_energy'] == 45) &
(df['total_exact_mass'] <= 800) &
(df['instrument_type_id'] == metadata['instrument_type_id']['labels'].index('ESI-QFT')) &
(df['ionization_mode_id'] == 1) &
(df['precursor_type_id'] == 2)
]
# df = df[
# (df['collision_energy'] <= 100) &
# (df['total_exact_mass'] >= 248.14) & (df['total_exact_mass'] <= 249) &
# (df['instrument_type_id'] == metadata['instrument_type_id']['labels'].index('ESI-QFT')) &
# (df['ionization_mode_id'] == 1) &
# (df['precursor_type_id'] == 2)
# ]
display(df.groupby('total_exact_mass')['total_exact_mass'].value_counts())
display(df.groupby('collision_energy')['collision_energy'].value_counts())
display(df)
total_exact_mass total_exact_mass
100.063663 100.063663 1
101.084064 101.084064 1
102.042927 102.042927 1
103.063329 103.063329 1
108.021129 108.021129 1
..
793.424856 793.424856 1
794.445257 794.445257 2
796.257850 796.257850 1
796.424521 796.424521 1
798.221858 798.221858 1
Name: total_exact_mass, Length: 1306, dtype: int64
collision_energy collision_energy 45.0 45.0 2020 Name: collision_energy, dtype: int64
| Unnamed: 0 | spectrum | SMILES | instrument | library | author | publication | structural_key | CASMI | split | ... | instrument_type_id | precursor_type_id | kingdom | superclass | class | subclass | kingdom_id | superclass_id | class_id | subclass_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7 | 7 | 50.324020:0.082640 53.391678:0.139188 53.64664... | O=C1OC=2C=C3OC(CC3=CC2C=C1C(C=C)(C)C)C(OC(=O)C... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | AWMHMGFGCLBSAY | NaN | train | ... | 0 | 2 | Organic compounds | Phenylpropanoids and polyketides | Coumarins and derivatives | Furanocoumarins | 1 | 18 | 70 | 184 |
| 40 | 40 | 50.102462:0.030662 50.656106:0.018519 52.22772... | OC1CC(=C)C2CC(CCC2(C)C1)C(O)(C)C | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | XZXBGGYJQALVAW | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Sesquiterpenoids | 1 | 6 | 198 | 420 |
| 57 | 57 | 50.485123:0.081488 50.517600:0.042573 50.69720... | O=C(OC1OC(COC(=O)C(=C)C(O)CO)C(O)C(O)C1O)C=CC=... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | MYWZGSROPRXVPM | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Saccharolipids | NaN | 1 | 6 | 233 | -1 |
| 81 | 81 | 50.076575:0.034197 50.109663:0.030391 50.29509... | O=C(O)C1=COC(OC2OC(CO)C(O)C(O)C2O)C3C(=CCC13)C... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | VTQUQEWGIJRVHB | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Terpene glycosides | 1 | 6 | 198 | 446 |
| 107 | 107 | 50.552747:0.031329 50.641198:0.056595 51.01399... | O=C1OC=C(C=C1)C2CCC3(O)C4CCC5=CC(OC6OC(CO)C(OC... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | KKOLMSSIDZXPLS | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Steroids and steroid derivatives | Steroid lactones | 1 | 6 | 238 | 429 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 120096 | 120096 | 50.089174:0.032204 50.554096:0.041443 50.78207... | O=C1C=2C=CC=CC2OC3=CC=C(OC)C=C31 | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | DVZCOQQFPCMIPO | NaN | train | ... | 0 | 2 | Organic compounds | Organoheterocyclic compounds | Benzopyrans | 1-benzopyrans | 1 | 14 | 43 | 11 |
| 120102 | 120102 | 50.545992:0.016675 50.726476:0.012751 50.73288... | C=1C=CC2=C(C1)NC(=C2CN(C)C)C | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | AJNMXMZCRHTBEH | NaN | train | ... | 0 | 2 | Organic compounds | Organoheterocyclic compounds | Indoles and derivatives | Indoles | 1 | 14 | 124 | 237 |
| 120552 | 120552 | 50.410845:0.037718 50.494566:0.034605 51.04280... | O=C1OC2C(C1=C)CCC3(C)C(O)CCC(=C)C23 | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | FKBUODICGDOIGB | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Terpene lactones | 1 | 6 | 198 | 447 |
| 124856 | 124856 | 50.608265:0.029362 50.744311:0.032188 50.87971... | O1C2=CC=C(C=C2OC1)C3OCC4C(OCC34)C5=CC=C6OCOC6=C5 | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | PEYUIKBAABKQKQ | NaN | train | ... | 0 | 2 | Organic compounds | Lignans, neolignans and related compounds | Furanoid lignans | NaN | 1 | 5 | 99 | -1 |
| 125730 | 125730 | 50.482665:0.152603 50.993602:0.116259 52.11490... | O=C(OC1CCC2(C)C(CCC3(C)C2CC=C4C5C(C)C(C)CCC5(C... | Thermo Q Exactive HF | Vaniya/Fiehn Natural Products Library | Arpana Vaniya | NaN | HLBZSQOUBVLLLL | NaN | train | ... | 0 | 2 | Organic compounds | Lipids and lipid-like molecules | Prenol lipids | Triterpenoids | 1 | 6 | 198 | 467 |
2020 rows × 31 columns
from scipy import stats
from specvae.jointvae import JointVAE
from specvae.vae import SpecVEA
# cc = model.config['cont_capacity']
# cols, vals = ['model_name', 'min_capacity', 'max_capacity', 'num_iter', 'gamma_z'], [model_name] + cc
from sklearn.metrics import r2_score, mean_squared_error, explained_variance_score
from sklearn.linear_model import LinearRegression
for model_path in model_dirs:
print("-------------------------------------------")
print(model_path)
model = load_model(model_path, device)
data = preload_data_as_tensor(df, input_columns=model.config['input_columns'], types=model.config['types'], transform=model.transform)
data_np = evaluate_model(model, df, data)
for target_column in labels:
print(target_column)
if isinstance(model, SpecVEA):
n_dim = data_np['z'].shape[1]
elif isinstance(model, JointVAE):
n_dim = model.config['latent_spec']['cont']
def plot_reg(df, ax, data_np, dim=0):
df['z'] = data_np['z'][:,dim]
slope, intercept, r_value, p_value, std_err = stats.linregress(df[target_column], df['z'])
x, y = df[target_column].to_numpy().reshape(-1,1), df['z'].to_numpy().reshape(-1,1)
reg = LinearRegression().fit(x, y)
y_ = reg.predict(x)
r2_value = r2_score(y, y_)
rmse_value = mean_squared_error(y, y_, squared=False)
exp_variance_value = explained_variance_score(y, y_)
pearson_value, pp = stats.pearsonr(df[target_column], df['z'])
spearman_value, sp = stats.spearmanr(df[target_column], df['z'])
print("r^2", r2_value)
print("RMSE", rmse_value)
print("explained variance", exp_variance_value)
print("Pearson", pearson_value, "p=", pp)
print("Spearman", spearman_value, "p=", sp)
print("-----------------")
if target_column == 'collision_energy':
sns.boxplot(x=target_column, y='z', data=df, ax=ax)
else:
sns.regplot(x=target_column, y='z',
data=df, color='blue', scatter_kws={'s': 5}, ax=ax,
line_kws={'label':"z[{0}] = {1:.2f} + {2:.3f}*10^-3 * {3}".format(dim, intercept, slope * 1000., target_column)})
ax.legend(fontsize=16)
fig, axs = plt.subplots(1, n_dim, figsize=(15 * n_dim, 10))
if n_dim == 1:
plot_reg(df, axs, data_np, 0)
else:
for dim, ax in enumerate(axs):
plot_reg(df, ax, data_np, dim)
sns.despine(right = True)
plt.show()
plt.clf()
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-800-200-50-3-50-200-800-20_01 (24-12-2021_01-50-12) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 2.2407520283707072e-10 RMSE 0.7130690211532243 explained variance 1.3586660463360545e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -4.526317098907384e-10 RMSE 0.7239071259738757 explained variance 1.2601870280626315e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.3657875658500416e-10 RMSE 0.547170163583552 explained variance 5.235335032161004e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
total_exact_mass r^2 0.021823838813307628 RMSE 0.7052451473275907 explained variance 0.021823851884270273 Pearson 0.14772893621130145 p= 2.5213623554259986e-11 Spearman 0.1876216418686893 p= 1.848476749623805e-17 ----------------- r^2 0.0009629184272912372 RMSE 0.723558510112167 explained variance 0.0009630447768440575 Pearson -0.031030934234844727 p= 0.16327549192678856 Spearman -0.018014758568226992 p= 0.4183844782237608 ----------------- r^2 0.01657196016018403 RMSE 0.5426173815130683 explained variance 0.016572011878595028 Pearson 0.1287321264985634 p= 6.383712948763486e-09 Spearman 0.129280094051818 p= 5.499489451178275e-09 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-400-100-3-400-20_02 (24-12-2021_03-34-34) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 5.606461628282489e-09 RMSE 0.5659636620896589 explained variance -3.878205689922254e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -4.5372148260725e-09 RMSE 0.4098775236886035 explained variance -2.3348817990154203e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -6.29886809377922e-10 RMSE 0.7632169389694899 explained variance 7.220333553270564e-09 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.022036625587697145 RMSE 0.5596929602668065 explained variance 0.022036582177351494 Pearson -0.14844736476200251 p= 2.0150332560878555e-11 Spearman -0.1759667925663201 p= 1.6380929585253068e-15 ----------------- r^2 0.03172431508131246 RMSE 0.40332358217342296 explained variance 0.031724296866494694 Pearson -0.17811322094271165 p= 7.335229954481528e-16 Spearman -0.17123730171007595 p= 9.284256943590396e-15 ----------------- r^2 0.002194809650291285 RMSE 0.7623789207028298 explained variance 0.0021948174832820966 Pearson 0.04684880231975681 p= 0.03525263371092355 Spearman 0.07315630309129635 p= 0.0010006600134110665 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-1600-3-1600-20_03 (24-12-2021_00-17-31) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -4.3453780573798895e-09 RMSE 0.18640058202843077 explained variance -4.573590750567291e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.0578784959136556e-08 RMSE 0.2950896198949129 explained variance 1.0963771879257678e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -7.898384168925077e-10 RMSE 0.7459575881764261 explained variance 4.996233260445848e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.00197237744668044 RMSE 0.1862166647386782 explained variance 0.0019723361377889104 Pearson 0.04441150508018927 p= 0.04595590440351965 Spearman 0.04468391944172824 p= 0.04463773825544379 ----------------- r^2 0.05651683384586503 RMSE 0.2866295838712 explained variance 0.05651692730630231 Pearson -0.23773267311196272 p= 2.380053479610822e-27 Spearman -0.2665723024055174 p= 3.311488497534173e-34 ----------------- r^2 0.0024753606503545855 RMSE 0.7450337587951218 explained variance 0.002475411276895545 Pearson -0.04975300431368653 p= 0.025343901371907188 Spearman -0.07742201010961826 p= 0.000496270973517602 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-800-3-800-20_04 (24-12-2021_00-25-10) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 2.703607338006009e-10 RMSE 0.0022009077890077057 explained variance 1.2649512992624068e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
r^2 4.265267361525105e-09 RMSE 0.011449216628138404 explained variance 5.912020861753575e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.0477867018465759e-08 RMSE 0.7468744242328453 explained variance 8.433612752600794e-08 Pearson nan p= nan Spearman nan p= nan -----------------
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.027370900951779298 RMSE 0.0021705783991859988 explained variance 0.027370912992103036 Pearson 0.16544153253889618 p= 7.281735947399276e-14 Spearman 0.15770450839668043 p= 1.016919519775211e-12 ----------------- r^2 0.07679300230573971 RMSE 0.011000826554788018 explained variance 0.07679305294820549 Pearson -0.2771154964414928 p= 6.180147334592307e-37 Spearman -0.2795104203278223 p= 1.4259414739508846e-37 ----------------- r^2 0.0023401805144430687 RMSE 0.7460000057777367 explained variance 0.0023402541998627235 Pearson 0.04837530424809769 p= 0.029695629706232747 Spearman 0.0764333679589902 p= 0.0005856890417460809 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_20-100-3-90-100-20_05 (24-12-2021_03-01-19) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 2.4822001787327963e-08 RMSE 0.007161226958334093 explained variance 1.0160154495508777e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.1713238157184946e-09 RMSE 0.008121850562963103 explained variance 1.3574548041184187e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.756732064845835e-08 RMSE 0.6907985796481347 explained variance 7.511619493083543e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.004805891390014527 RMSE 0.007143998282684944 explained variance 0.004805876798630093 Pearson -0.069324358542318 p= 0.0018235181601310168 Spearman -0.08484787060084734 p= 0.0001345579236071274 ----------------- r^2 0.0004445793725845748 RMSE 0.00812004496339903 explained variance 0.0004445917702946556 Pearson 0.021085023162935687 p= 0.3435508183468507 Spearman 0.07185195831798268 p= 0.0012313272644689456 ----------------- r^2 0.0026628109484545526 RMSE 0.6898782430613305 explained variance 0.0026628583707164477 Pearson -0.051602165211738896 p= 0.020376687310682283 Spearman -0.07934663278120498 p= 0.00035751413111371767 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\best\betavae_capacity_50-400-3-100-400-50_06 (24-12-2021_06-19-49) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.3295018136693102e-08 RMSE 0.6518542767732731 explained variance -6.008607122964804e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.278918920239903e-08 RMSE 0.005903318812437642 explained variance 1.3223125405747993e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.620704619982206e-08 RMSE 0.016138581117958913 explained variance 6.233418747836339e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.009801437898350307 RMSE 0.6486518482061565 explained variance 0.009801401467903315 Pearson -0.09900232807890584 p= 8.280430428141932e-06 Spearman -0.13561914700328936 p= 9.366751502825198e-10 ----------------- r^2 0.006825866723587759 RMSE 0.005883136746643715 explained variance 0.006825975418617847 Pearson -0.08261866671614797 p= 0.00020135917111584352 Spearman -0.0784464583539966 p= 0.0004171542158565091 ----------------- r^2 0.006990426002617345 RMSE 0.016082074625478143 explained variance 0.006990461877215415 Pearson -0.08360861186964236 p= 0.00016855873622471617 Spearman -0.11733907989748175 p= 1.2315491795987792e-07 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_01 (24-12-2021_09-13-36) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -4.365010353168941e-09 RMSE 0.3635213194796388 explained variance -4.100135320150855e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.1445204117777052e-08 RMSE 1.0366927058223785 explained variance -5.4648418013059086e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 3.175440022040732e-09 RMSE 0.6442409243316954 explained variance -1.0877754252902605e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.1896819812859255 RMSE 0.3272334063939012 explained variance 0.18968195159883705 Pearson 0.43552495315764883 p= 2.772635439155604e-94 Spearman 0.4848856644179108 p= 1.294524900576106e-119 ----------------- r^2 0.0013477600115259225 RMSE 1.035993857859995 explained variance 0.0013477168665401162 Pearson 0.03671200677305064 p= 0.09903824297151624 Spearman 0.07052150002102286 p= 0.0015163588759716093 ----------------- r^2 0.023771879825483566 RMSE 0.6365374596003015 explained variance 0.023771866106360173 Pearson -0.1541813112070644 p= 3.2378009583857296e-12 Spearman -0.17349212764246139 p= 4.085018614552594e-15 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_02 (24-12-2021_09-15-11) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -9.241277743043952e-09 RMSE 0.9849810022870527 explained variance -3.096691347792557e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.1856609855319675e-09 RMSE 0.4366854702223464 explained variance -9.916189425140942e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.017599116082124e-09 RMSE 0.4014774462521458 explained variance 4.436644862604311e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.003140545292897312 RMSE 0.983433092745672 explained variance 0.0031405236354917765 Pearson 0.056040650470459655 p= 0.011764364515988222 Spearman 0.08680187526320504 p= 9.375166616737013e-05 ----------------- r^2 0.10465140348286717 RMSE 0.4132042883056913 explained variance 0.10465139656134947 Pearson -0.32349869464929193 p= 1.9852647225248718e-50 Spearman -0.35486027178043383 p= 5.24950538583887e-61 ----------------- r^2 0.09795339674324743 RMSE 0.3813077572012243 explained variance 0.09795343768177356 Pearson -0.3129750751436436 p= 3.7843725608658163e-47 Spearman -0.33989752337195744 p= 8.308834114101926e-56 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_03 (24-12-2021_09-29-26) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -3.968192663350578e-09 RMSE 0.38969834055998126 explained variance 9.971279868459249e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -7.441549598752317e-10 RMSE 0.9683292837348609 explained variance -1.4447091523095423e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.946257238178873e-09 RMSE 0.3532340166761987 explained variance -6.231621441088464e-09 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.12126011985014629 RMSE 0.365307613751269 explained variance 0.12126021095876793 Pearson -0.34822424289120846 p= 1.1510660271765272e-58 Spearman -0.37894993437683444 p= 5.479709057243049e-70 ----------------- r^2 0.0024956062794124767 RMSE 0.9671202442618924 explained variance 0.002495592610673003 Pearson 0.04995605090186911 p= 0.02475161581365196 Spearman 0.08136659860427255 p= 0.00025144740285744545 ----------------- r^2 0.08462539241619438 RMSE 0.33795739168279576 explained variance 0.08462538940885544 Pearson -0.29090444326810033 p= 1.0880014474357853e-40 Spearman -0.3157672946580805 p= 5.254130966404419e-48 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_04 (24-12-2021_09-29-36) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 6.281701825372465e-10 RMSE 0.5961026484460442 explained variance -9.131341482948585e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.3550480615929246e-08 RMSE 0.07270293797385924 explained variance -1.0867278588122531e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 4.2660155408213996e-09 RMSE 0.5046821982086996 explained variance -1.340301003516231e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.019161662222265674 RMSE 0.5903638657056993 explained variance 0.019161572042434183 Pearson -0.13842565371394183 p= 4.16520198760197e-10 Spearman -0.19082013904701658 p= 5.12323642296533e-18 ----------------- r^2 0.07631488132304098 RMSE 0.06987373001466053 explained variance 0.07631481193368805 Pearson -0.2762515381190114 p= 1.0452116085895133e-36 Spearman -0.3199566010753723 p= 2.609862231180263e-49 ----------------- r^2 0.026722623054909467 RMSE 0.4978933219327626 explained variance 0.026722605858046533 Pearson 0.16347054445034837 p= 1.4429143967701253e-13 Spearman 0.1545288067747041 p= 2.8917031904811392e-12 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_05 (24-12-2021_09-06-14) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.9097034620330078e-08 RMSE 0.5887295519432438 explained variance 4.0835606451850026e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.5809666908950248e-09 RMSE 0.23324879650197927 explained variance -1.854287301483737e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -7.602525942118632e-09 RMSE 0.004572875690035685 explained variance 5.0504722293176485e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.017300086028593897 RMSE 0.5836148036349883 explained variance 0.017300107391086894 Pearson -0.13152972007093738 p= 2.9625235471922435e-09 Spearman -0.1863417647383604 p= 3.0693208156119744e-17 ----------------- r^2 0.07510424612116773 RMSE 0.22431886803971499 explained variance 0.07510422750871393 Pearson 0.27405153650169223 p= 3.950084005445035e-36 Spearman 0.2736240609923027 p= 5.107207082265251e-36 ----------------- r^2 0.07168811895459526 RMSE 0.004405917373700326 explained variance 0.07168817289624374 Pearson 0.267746383751696 p= 1.667676825421064e-34 Spearman 0.2645627447211918 p= 1.062842868829097e-33 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\beta\betavae_capacity_100-1600-200-50-3-50-200-1600-100_06 (24-12-2021_09-05-10) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.946203764813248e-08 RMSE 0.007620827034797339 explained variance -3.081576527286245e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.891103217412706e-09 RMSE 0.002383122228690275 explained variance -1.8269823431893428e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.841050245587894e-08 RMSE 0.6156452922836865 explained variance 4.033078315757166e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.009943386268888799 RMSE 0.007582844039167654 explained variance 0.009943336491016419 Pearson 0.09971643295048804 p= 7.118410687734365e-06 Spearman 0.11334380177258822 p= 3.264778085381127e-07 ----------------- r^2 0.012651607943393595 RMSE 0.00236799907472891 explained variance 0.012651593746587197 Pearson 0.11247938382329555 p= 4.0142433189375337e-07 Spearman 0.15499789659411264 p= 2.4814205996925623e-12 ----------------- r^2 0.02063836681305986 RMSE 0.6092592198689055 explained variance 0.020638388280942332 Pearson -0.14366053314156893 p= 8.790365316458302e-11 Spearman -0.20220496564853105 p= 4.4198135236276054e-20 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-100-3-400-100_01 (24-12-2021_11-06-17) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.0626793606481897e-09 RMSE 0.9754296181064962 explained variance -1.618449485540907e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.9519965078227415e-10 RMSE 0.3530985363338203 explained variance -1.490727763453492e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.1569062374761074e-09 RMSE 0.426323575445529 explained variance -1.8256511635783568e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.010898126612971848 RMSE 0.9700998785443973 explained variance 0.0108981126450578 Pearson 0.10439410257850719 p= 2.5777822624038153e-06 Spearman 0.13562850107958221 p= 9.341740600257243e-10 ----------------- r^2 0.20522496528843026 RMSE 0.3147878965526002 explained variance 0.2052249537545927 Pearson 0.4530176217350985 p= 8.687531307870292e-103 Spearman 0.498506711439284 p= 2.2815970297131757e-127 ----------------- r^2 0.006028971433156283 RMSE 0.42503648647370773 explained variance 0.006028952136781673 Pearson 0.07764644411191814 p= 0.0004778275283825092 Spearman 0.08097111189833042 p= 0.0002695532102878488 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-800-100-3-800-100_02 (24-12-2021_10-59-29) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 2.5194192287969486e-09 RMSE 0.43140950096655656 explained variance 2.515894736987434e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -2.3649675551240534e-09 RMSE 1.0392320442252818 explained variance 1.835318919063411e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -5.067117836432544e-10 RMSE 0.7134327757095345 explained variance -6.127286611423699e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.011641215948359873 RMSE 0.42889108511237206 explained variance 0.01164123832433639 Pearson 0.1078944551785209 p= 1.171220038982501e-06 Spearman 0.11480105329979577 p= 2.2964509824626115e-07 ----------------- r^2 0.018172398332876538 RMSE 1.0297460804135738 explained variance 0.018172418674534785 Pearson -0.13480504684494282 p= 1.1812616903609634e-09 Spearman -0.16588003804742557 p= 6.246865713732163e-14 ----------------- r^2 0.12565432780964658 RMSE 0.667105681763809 explained variance 0.1256542746790228 Pearson -0.3544775426634076 p= 7.188968252285757e-61 Spearman -0.3778826794043316 p= 1.4225975647408052e-69 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-200-50-3-50-200-400-100_03 (24-12-2021_09-47-19) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.021891543080301e-09 RMSE 0.3945325749848203 explained variance -1.5523382135285146e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.5165191819276345e-08 RMSE 0.32103005778076127 explained variance 6.908423033635813e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.2073823274505457e-08 RMSE 0.9945692293010269 explained variance 3.682679317051907e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.04313435129413923 RMSE 0.3859298302505017 explained variance 0.04313433837502689 Pearson 0.20768811528062386 p= 4.03636514850342e-21 Spearman 0.23553145392121203 p= 7.313719132798376e-27 ----------------- r^2 0.17308854586878475 RMSE 0.2919276332003165 explained variance 0.1730885821859418 Pearson 0.41603909078282414 p= 2.2152369949737835e-85 Spearman 0.47132146470236924 p= 3.109574997244047e-112 ----------------- r^2 0.0035434206319843176 RMSE 0.992805571017083 explained variance 0.0035434693593248134 Pearson 0.05952673905922421 p= 0.0074481896375146696 Spearman 0.09223241592055305 p= 3.3013405278126573e-05 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.9282920532835988e-09 RMSE 0.5468713729323084 explained variance -8.833791564910598e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -7.3255697063956404e-09 RMSE 0.7442257747791382 explained variance 8.126284656295724e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.6074137576538305e-09 RMSE 0.13010732378815965 explained variance -5.962727400721235e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.03623216221698233 RMSE 0.5368728029826426 explained variance 0.03623207990193422 Pearson 0.19034748498253393 p= 6.201779687596873e-18 Spearman 0.24551392759611815 p= 4.100849563258918e-29 ----------------- r^2 0.0026211934206251675 RMSE 0.743249752200744 explained variance 0.0026212817768335173 Pearson -0.05119766329621969 p= 0.02138408042283741 Spearman -0.028739215045328066 p= 0.1966571410585067 ----------------- r^2 0.019712036155479784 RMSE 0.12881860131056427 explained variance 0.01971197612785225 Pearson 0.14039955334598214 p= 2.3324439343541573e-10 Spearman 0.16922491450866475 p= 1.9138608094890976e-14 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-100-3-400-100_05 (24-12-2021_10-57-01) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -3.141964466379932e-10 RMSE 0.6321746414900721 explained variance -3.769722378699214e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 3.7251086659750854e-09 RMSE 0.2522578582028822 explained variance 5.4936180049480754e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.8895914832839367e-08 RMSE 0.004719882045663122 explained variance 1.757540990521278e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.014860075503070003 RMSE 0.6274599793243184 explained variance 0.014860038675557408 Pearson 0.1219019106191436 p= 3.886662144148323e-08 Spearman 0.17620586455777265 p= 1.49861995094015e-15 ----------------- r^2 0.06372478949957561 RMSE 0.24408802156160467 explained variance 0.06372483744723245 Pearson -0.25243768738413186 p= 9.779716320636341e-31 Spearman -0.2608160833852879 p= 9.10083565265351e-33 ----------------- r^2 0.07587286027819728 RMSE 0.004537294864572437 explained variance 0.07587289398233754 Pearson 0.27545031809824577 p= 1.698650629211678e-36 Spearman 0.27162829056128346 p= 1.6844651906736226e-35 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\betavae_score\betavae_capacity_100-400-100-3-100-400-100_06 (24-12-2021_08-41-33) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 3.9494566506093065e-09 RMSE 0.5835055543445359 explained variance -4.0149739533035245e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.492829615479252e-08 RMSE 0.003078217826268953 explained variance 4.781739226800141e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -5.26099586117823e-09 RMSE 0.006343687170525701 explained variance 3.71774514507095e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.02160575993201308 RMSE 0.5771675939639099 explained variance 0.021605716785613294 Pearson -0.14698896580317705 p= 3.172574982427943e-11 Spearman -0.20267205435076222 p= 3.61421039030822e-20 ----------------- r^2 0.07861971860800954 RMSE 0.0029547368088446465 explained variance 0.07861973676844736 Pearson 0.2803921046724519 p= 8.280051510416833e-38 Spearman 0.26543845004952804 p= 6.401934949782583e-34 ----------------- r^2 0.01250650658311947 RMSE 0.006303893660401589 explained variance 0.012506548490809677 Pearson -0.11183251664126356 p= 4.680958377387473e-07 Spearman -0.10354969881179651 p= 3.106635573398333e-06 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-100-90-50-3-50-90-100-100_01 (24-12-2021_09-48-37) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -9.277010937225327e-09 RMSE 0.4742016974601038 explained variance 2.055246728360771e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.896079893093372e-08 RMSE 0.6944828348444806 explained variance -3.502520118381369e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 2.551940880834991e-10 RMSE 0.8664956920565837 explained variance 1.483916101108207e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.07745639480634248 RMSE 0.45546661948409456 explained variance 0.07745642232533645 Pearson -0.27830990525813026 p= 2.9795714150874384e-37 Spearman -0.32838973834750346 p= 5.3468256334042604e-52 ----------------- r^2 0.009656825291864068 RMSE 0.6911214438279621 explained variance 0.009656809382593057 Pearson 0.09826924274441869 p= 9.660683245328877e-06 Spearman 0.13649243337477573 p= 7.291876192489626e-10 ----------------- r^2 0.002015616591515834 RMSE 0.8656219901361902 explained variance 0.002015631146087271 Pearson -0.044895616009095266 p= 0.04363551309691559 Spearman -0.0200066949198817 p= 0.36880051025567473 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-1600-100-3-1600-100_02 (24-12-2021_10-51-41) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 1.1142713418621497e-09 RMSE 0.46680401836197494 explained variance 3.061454711961176e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -4.580984480639927e-10 RMSE 1.0256872686329406 explained variance 1.1808105715438444e-07 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -1.4465126874085854e-09 RMSE 0.43063052950346137 explained variance -6.235341754035062e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.0031656346338442276 RMSE 0.4660645674658435 explained variance 0.0031656640407329295 Pearson 0.05626396291677324 p= 0.011432647302658434 Spearman 0.06177740195134015 p= 0.005478164952077367 ----------------- r^2 0.010978820177057425 RMSE 1.0200413111033373 explained variance 0.010978937414792944 Pearson 0.10477986748477354 p= 2.3659962274783897e-06 Spearman 0.13671220976309253 p= 6.844816518150146e-10 ----------------- r^2 0.2147884274889995 RMSE 0.38159103358876073 explained variance 0.21478837966419306 Pearson -0.4634527253397243 p= 4.209291632690472e-108 Spearman -0.5056829978955839 p= 1.3479394315014284e-131 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-800-100-3-800-100_03 (24-12-2021_11-16-41) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 2.156494094407435e-09 RMSE 1.0138999021655255 explained variance -4.651818685807996e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.6050515361243356e-09 RMSE 0.41660595733973277 explained variance -4.980876888716068e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 6.148452857956954e-10 RMSE 0.3288737681946799 explained variance -2.741314286680563e-09 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.009988556597484655 RMSE 1.0088234966671237 explained variance 0.009988508408993457 Pearson 0.09994275592823526 p= 6.78387282941539e-06 Spearman 0.1355000699760536 p= 9.690898374861075e-10 ----------------- r^2 0.00010356533048394567 RMSE 0.41658438414864396 explained variance 0.00010351392198826304 Pearson -0.010176626435054317 p= 0.6475911250813381 Spearman -0.007139041584463634 p= 0.7484639021017987 ----------------- r^2 0.20936691357205683 RMSE 0.29242650043627744 explained variance 0.20936691091856596 Pearson -0.457566293651466 p= 4.414925673313788e-105 Spearman -0.49980053669847263 p= 4.0114582907134675e-128 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-1600-3-1600-100_04 (24-12-2021_08-02-44) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -2.9282920532835988e-09 RMSE 0.5468713729323084 explained variance -8.833791564910598e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -7.3255697063956404e-09 RMSE 0.7442257747791382 explained variance 8.126284656295724e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.6074137576538305e-09 RMSE 0.13010732378815965 explained variance -5.962727400721235e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.03623216221698233 RMSE 0.5368728029826426 explained variance 0.03623207990193422 Pearson 0.19034748498253393 p= 6.201779687596873e-18 Spearman 0.24551392759611815 p= 4.100849563258918e-29 ----------------- r^2 0.0026211934206251675 RMSE 0.743249752200744 explained variance 0.0026212817768335173 Pearson -0.05119766329621969 p= 0.02138408042283741 Spearman -0.028739215045328066 p= 0.1966571410585067 ----------------- r^2 0.019712036155479784 RMSE 0.12881860131056427 explained variance 0.01971197612785225 Pearson 0.14039955334598214 p= 2.3324439343541573e-10 Spearman 0.16922491450866475 p= 1.9138608094890976e-14 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-400-200-50-3-50-200-400-100_05 (24-12-2021_09-23-23) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 -1.4179062146624233e-08 RMSE 0.589163443876972 explained variance -4.0020488256686804e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 7.043721161892336e-11 RMSE 0.23886178577308392 explained variance 4.9243375377372445e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 -3.702339768096863e-09 RMSE 0.011536507604480438 explained variance -4.460740732348256e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.017352689257075782 RMSE 0.5840292843330296 explained variance 0.017352663864068196 Pearson 0.13172965949281418 p= 2.8026154308285774e-09 Spearman 0.18849249982005792 p= 1.3063623003918694e-17 ----------------- r^2 0.06448069098544396 RMSE 0.23103248674602875 explained variance 0.06448073698767709 Pearson -0.25393048442349037 p= 4.3040385900215e-31 Spearman -0.2599341359398924 p= 1.5011478405590525e-32 ----------------- r^2 0.07527851732567103 RMSE 0.011093787158717477 explained variance 0.07527847949987632 Pearson 0.2743693145184133 p= 3.2623610875619506e-36 Spearman 0.2759480881627193 p= 1.2564996695829022e-36 -----------------
<Figure size 432x288 with 0 Axes>
------------------------------------------- d:\Workspace\SpecVAE\.model\MoNA\betavae_capacity_nextron\factorvae_score\betavae_capacity_100-1600-100-3-100-1600-100_06 (24-12-2021_08-25-38) Encode N=2020 instances from MoNA dataset... torch.Size([2020, 3]) collision_energy r^2 4.852581225733843e-09 RMSE 0.00486468573487749 explained variance 5.308784811752787e-08 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.1768919838672787e-08 RMSE 0.0016611132191589563 explained variance -8.397357920131299e-09 Pearson nan p= nan Spearman nan p= nan ----------------- r^2 1.630386936568584e-08 RMSE 0.5779305663357301 explained variance 2.0971065106678566e-08 Pearson nan p= nan Spearman nan p= nan -----------------
d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:170: RuntimeWarning: invalid value encountered in double_scalars slope = ssxym / ssxm d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\_stats_mstats_common.py:187: RuntimeWarning: divide by zero encountered in double_scalars slope_stderr = np.sqrt((1 - r**2) * ssym / ssxm / df) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4023: PearsonRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(PearsonRConstantInputWarning()) d:\Workspace\anaconda3\envs\specvae\lib\site-packages\scipy\stats\stats.py:4484: SpearmanRConstantInputWarning: An input array is constant; the correlation coefficient is not defined. warnings.warn(SpearmanRConstantInputWarning())
<Figure size 432x288 with 0 Axes>
total_exact_mass r^2 0.0009915694542634856 RMSE 0.0048622733116125815 explained variance 0.0009916176417020806 Pearson 0.031489118858643764 p= 0.15714630832641824 Spearman -0.04028211972730333 p= 0.0702849149376726 ----------------- r^2 0.015552894371493098 RMSE 0.001648145048859421 explained variance 0.015552874518859006 Pearson -0.12471119751495381 p= 1.8705271580370787e-08 Spearman -0.12778456651795264 p= 8.249083461923692e-09 ----------------- r^2 0.022614003578295017 RMSE 0.5713585416069425 explained variance 0.02261400813994663 Pearson 0.15037947879654678 p= 1.0967564750831701e-11 Spearman 0.20813627405042645 p= 3.3092049181958036e-21 -----------------
<Figure size 432x288 with 0 Axes>
<Figure size 432x288 with 0 Axes>
# df2 = pd.DataFrame([vals], columns=cols)
# df2
# stats_file = "d:\\Workspace\\SpecVAE\\.model\\MoNA\\joint_vae_%d_stats.csv" % n_dim
# if os.path.exists(stats_file):
# df = pd.read_csv(stats_file, index_col=0)
# df = pd.concat([df, df2], ignore_index=True)
# df.to_csv(stats_file)
# else:
# df2.to_csv(stats_file)